DUGiDocsA review of personalized blood glucose prediction strategies for T1DM patients
dc.contributor.author
dc.date.accessioned
2017-02-03T07:39:24Z
dc.date.available
2017-02-03T07:39:24Z
dc.date.issued
2017-06
dc.identifier.issn
2040-7939
dc.identifier.uri
dc.description.abstract
This paper presents a methodological review of models for predicting blood glucose (BG) concentration, risks and BG events. The surveyed models are classified into three categories, and they are presented in summary tables containing the most relevant data regarding the experimental setup for fitting and testing each model as well as the input signals and the performance metrics. Each category exhibits trends that are presented and discussed. This document aims to be a compact guide to determine the modeling options that are currently being exploited for personalized BG prediction
dc.description.sponsorship
This work has been funded by the Spanish Government through the predoctoral contract ES‐2014‐068289 within the project ‘New methods for efficiency and safety of home artificial pancreas in type I diabetes’ with reference number DPI2013‐46982‐C2‐2‐R
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Wiley
dc.relation
DPI2013‐46982‐C2‐2‐R
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Reproducció digital del document publicat a: http://dx.doi.org/10.1002/cnm.2833
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© International Journal for Numerical Methods in Biomedical Engineering, 2017, vol. 33, núm. 6, p. e2833
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Articles publicats (D-EEEiA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
A review of personalized blood glucose prediction strategies for T1DM patients
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/embargoedAccess
dc.embargo.terms
Cap
dc.date.embargoEndDate
info:eu-repo/date/embargoEnd/2026-01-01
dc.relation.projectID
info:eu-repo/grantAgreement/MINECO//DPI2013-46982-C2-2-R/ES/NUEVOS METODOS PARA LA EFICIENCIA Y SEGURIDAD DEL PANCREAS ARTIFICIAL DOMICILIARIO EN DIABETES TIPO 1/
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
026104
dc.contributor.funder
dc.relation.FundingProgramme
dc.relation.ProjectAcronym
dc.identifier.eissn
2040-7947